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Why Small Businesses Are the Real Winners of the AI Boom

Updated: 3 hours ago

You could be forgiven for assuming that artificial intelligence is a tool built only for enterprises with Chief Innovation Officers, digital transformation budgets, and TED Talk ambitions. After all, that’s where most consultants pitch their tents: sprawling organizations with enough bloat they can spend millions for someone to write pitch decks about it.


But as usual in the business of ideas, a lot of consultants have it backwards.

Today, the companies best positioned to benefit from AI aren't the ones hiring McKinsey to help them figure it out. They are the ones answering their own phones, formatting their own PDFs, and spending their Friday mornings wrestling with 23 versions of a client report.


They are small businesses. And there are a lot of them.



The Weight of the Real Economy


Small and mid-sized businesses (SMBs) comprise 90% of all firms globally and more than half of all jobs1. In the United States, 33.3 million small businesses account for 99.9% of companies and nearly 46% of employment2.


In other words: they are the economy. And unlike their enterprise cousins, they operate without the cushion of large IT teams, internal data science, or management layers that could safely absorb failed experiments.


What most Consultants Don’t See


The consulting class tends to view AI through the same lens it uses for everything: top-down, tech-forward, and allergic to simplicity. Strategy decks abound. So do roadmaps and workshops. Outcomes, not so much.


But most small businesses don’t need a complicated strategy. They need relief.


A CPA firm doesn’t need to “define its AI vision.” It needs to extract data from a stack of 1099s without spending six hours and two Advil3.


A financial advisor doesn’t need another “platform.” She needs to summarize performance narratives for 40 client portfolios, then actually make it home for dinner4.

An insurance agency doesn’t need a chatbot. It needs to stop retyping client data into five different portals because one portal still requires Internet Explorer5.


The pattern is the same: manual work, repeated endlessly, not because it’s necessary, but because no one has the time to stop and fix it.




AI at the Edge


The term “edge computing” refers to moving computation closer to the source of data. In practice, it means skipping the central server and putting intelligence where the action is.


AI, applied properly, should work similarly


Most small businesses don't need a complete technology overhaul. They need an overlay. Something lightweight that automates the things you and your staff quietly dread doing.

The best tools are not disruptive. They are basically invisible until they start saving you time.



The Danger of Overpromising


If this sounds refreshingly modest, that’s intentional.


A lot of what passes for “AI thought leadership” suffers from what we might call inverse specificity: the grander the promise, the foggier the deliverable. There is a long history of overbuilt solutions created for problems that weren’t there, often funded by people who didn’t understand them.

There is no virtue in complexity. The real art lies in precision: one process, well-understood, improved to remove real pain.



A Note of Caution (And Opportunity)


AI isn’t magic. It requires judgment, boundaries, and a clear understanding of what is not worth doing.


It's math. And for small businesses that know where they bleed time and focus, AI is actually cheap and accurate enough to do something about it today.


Contact US, If you're a small business owner trying to figure out how generative AI can help you.





Pure Math Editorial is an all-purpose virtual writer we created to document and showcase the various ways we are leveraging generative AI within our organization and with our clients. Designed specifically for case studies, thought leadership articles, white papers, blog content, industry reports, and investor communications, it is prompted to ensure clear, compelling, and structured writing that highlights the impact of AI across different projects and industries.



Endnotes


  1. World Bank, SME Finance. “Small and Medium Enterprises (SMEs) Finance.” https://www.worldbank.org/en/topic/smefinance ↩

  2. U.S. Small Business Administration. “2023 Small Business Economic Profile – United States.” https://advocacy.sba.gov/wp-content/uploads/2023/11/2023-Small-Business-Economic-Profile-US.pdf ↩

  3. TruePrep.ai. “Tax Preparation Automation for Accountants.” https://www.trueprep.ai/tax-preparation-automation-for-accountants ↩

  4. SmartAsset. “AI and the RIA.” https://smartasset.com/advisor-resources/ai-ria ↩

  5. Semsee. “How AI Is Changing the Quoting Process for the Insurance Industry.” https://semsee.com/blog/how-is-ai-changing-the-quoting-process-for-the-insurance-industry ↩

  6. World Bank, SME Finance. “Small and Medium Enterprises (SMEs) Finance.” https://www.worldbank.org/en/topic/smefinance ↩

  7. U.S. Small Business Administration. “2023 Small Business Economic Profile – United States.” https://advocacy.sba.gov/wp-content/uploads/2023/11/2023-Small-Business-Economic-Profile-US.pdf ↩

  8. TruePrep.ai. “Tax Preparation Automation for Accountants.” https://www.trueprep.ai/tax-preparation-automation-for-accountants ↩

  9. SmartAsset. “AI and the RIA.” https://smartasset.com/advisor-resources/ai-ria ↩

  10. Semsee. “How AI Is Changing the Quoting Process for the Insurance Industry.” https://semsee.com/blog/how-is-ai-changing-the-quoting-process-for-the-insurance-industry ↩

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